JP5497770B2 - A method for distinguishing and predicting atherothrombotic cerebral infarction in acute cerebral infarction - Google Patents

Description

  The present invention relates to a method for measuring glycoalbumin and hemoglobin A1c in a biological sample of a patient with acute cerebral infarction, and accurately, simply, rapidly and inexpensively distinguishing the type of acute cerebral infarction from the glycoalbumin / hemoglobin A1c ratio, In addition, the present invention relates to a method for measuring the occurrence of atherothrombotic cerebral infarction accurately, simply, quickly and inexpensively by measuring glycoalbumin and hemoglobin A1c in a biological sample of a subject and determining the ratio of glycoalbumin / hemoglobin A1c and / or its change with time. Furthermore, the present invention relates to a device for identifying the type of atherothrombotic cerebral infarction in an acute stage cerebral infarction patient or predicting the onset of atherothrombotic cerebral infarction in a subject, and atherothrombotic cerebral infarction in an acute stage cerebral infarction patient The present invention relates to a kit for diagnosing atherothrombotic cerebral infarction for predicting the onset of atherothrombotic cerebral infarction or for predicting the onset of atherothrombotic cerebral infarction in a subject.

  Cerebral infarction is classified into four clinical types (NINDS “Classification of Cerebrovascular Disorders III”) in the acute phase, although it is classified clinically as atherothrombotic cerebral infarction, cardiogenic cerebral embolism, lacunar infarction. It is very important to identify these disease types as early as possible in cerebral infarction because the applicable drugs and treatment methods differ depending on the disease type (Non-patent Document 1). For example, among the acute cerebral infarctions, ozagrel, an anticoagulant drug that is indicated for atherothrombotic cerebral infarction, and argatroban, an antiplatelet drug, are contraindicated for cardiogenic cerebral infarction. Is important.

  Conventionally, these types of acute cerebral infarction are identified by history, physical findings, clinical symptoms, diagnostic imaging such as CT / CTA, MRI / MRA, electrocardiogram, platelet function, blood tests for coagulation / fibrinolysis, and local blood flow in the brain. This is done by comprehensively judging the results of inspections. At present, the most widely used CT-based determination differs depending on the determiner at an early stage, and since the correct diagnosis rate for non-skilled physicians is low, in recent years diagnosis by DWI has become widespread. However, each method requires an expensive device, is highly specialized and complicated, and is often difficult to make a definitive diagnosis, and an accurate, simple, quick, and inexpensive method for identifying a disease type is required. It was.

  According to Non-Patent Document 2, in the diagnosis of atherothrombotic cerebral infarction, findings characteristic of atherothrombotic cerebral infarction (histologic risk factors, other atherosclerotic diseases, etc.) are obtained through medical history, examination, and imaging. It is important whether or not it is possible to obtain complications, TIA precedent, staged symptom progression after onset, cervical vascular noise, disturbance of consciousness, cortical symptoms, borderline or cortical branch infarction, but cerebral infarction is necessary for definitive diagnosis It is necessary to prove the existence of a stenosis (more than 50% of the blood vessel diameter) or occlusion of the main artery that causes the above-mentioned cause. However, there are many cases where it is difficult to prove the presence of stenosis or occlusion of the main artery necessary for definitive diagnosis using CT, CTA, MR, or MRA, and even examinations other than facilities having these expensive devices can be performed. Impossible.

  In the diagnosis of cardiogenic cerebral infarction, the most frequent non-valvular atrial fibrillation (NVAF) is said to require an electrocardiogram, but 1/3 of NVAF is seizure, If it is not a time record, there is a possibility of missing an abnormality. In addition, the incidence of sudden complete type is “80 to 90% of the frequency”, “not less” is accompanied by consciousness disorder than at the time of onset, and consciousness disorder in the course is often “severe”, aphasia and disapproval Cortical disorders such as "is easy to present", and the type of disease cannot be determined immediately from these physical symptoms.

  As mentioned above, in acute cerebral infarction, there is no unified rule for disease type differentiation, although the differentiation of disease type is very important because of different treatment methods. Judgment is necessary and is often difficult even in situations where these are met.

  By the way, in the diagnosis of diabetes and blood glucose management, glycated proteins such as hemoglobin A1c and glycoalbumin are routinely measured in clinical practice and are widely used as blood glucose management indices. Hemoglobin A1c is a substance in which glucose is bound to hemoglobin in erythrocytes, and the amount of hemoglobin A1c is determined by the blood glucose state of hemoglobin for about 4 months, mainly 2 months. On the other hand, glycoalbumin is a substance in which glucose is bound to serum and plasma albumin, and the amount of albumin is determined by the blood glucose state of about 1 month, mainly 2 weeks, during the period in which albumin is present in the blood. That is, glycoalbumin is an index that represents a more recent blood glucose state than hemoglobin A1c.

  It is known that the values of hemoglobin A1c and glycoalbumin are characteristic values in which the ratio of glycoalbumin / hemoglobin A1c is about 3 when blood sugar is stable (Non-patent Document 3). When changed, glycoalbumin fluctuates in advance, and the ratio changes from a characteristic value of about 3. Glycoalbumin rises in advance in a state in which the blood sugar state is worsening, so that the ratio of glycoalbumin / hemoglobin A1c is larger than the characteristic value of about 3 when blood sugar is stable, and the blood sugar state is improved The ratio is smaller than a characteristic value of about 3. Therefore, it is possible to determine whether the latest blood glucose level is rising or falling based on the ratio of glycoalbumin / hemoglobin A1c.

  The glycoalbumin / hemoglobin A1c ratio changes from a characteristic value of about 3 not only when the blood sugar fluctuates but also when the blood sugar is stable, even when the daily blood sugar fluctuation is large. For example, it has been reported that glycoalbumin / hemoglobin A1c is high in the former in patients with type 1 diabetes with severe blood glucose fluctuations and in patients with type 2 diabetes with relatively little fluctuations (Non-patent Document 4). In addition, since glycoalbumin more closely reflects postprandial hyperglycemia and hemoglobin A1c more reflects fasting blood glucose, there is also a report that blood sugar fluctuation width can be predicted from the difference between the two (Non-patent Document 5). From this report, it is presumed that the glycoalbumin / hemoglobin A1c ratio is larger than a characteristic value of about 3 even in the case of type 2 diabetic patients even when the blood sugar fluctuation is large. In relation to diabetic complications, a report that the ratio of glycoalbumin / hemoglobin A1c is related to the severity of retinopathy (Non-Patent Document 6), and the relationship between glycoalbumin and the presence or absence of coronary artery disease, and the severity It has been reported (Non-Patent Document 7). Even in diseases such as cirrhosis, renal failure, thyroid disease, anemia, etc., which affect the life span of hemoglobin and the half-life of albumin, the characteristic of having a glycoalbumin / hemoglobin A1c ratio of about 3 regardless of blood glucose fluctuations It has also been reported that the value deviates (Non-patent Document 8).

  As described above, it has been reported that the ratio of glycoalbumin / hemoglobin A1c is not merely a glycemic index, but deviates from a characteristic value of about 3 due to various pathological conditions, and various pathological conditions are determined based on the degree of the divergence. Although it has been reported that it may be possible (Non-patent Document 9), there has been no report on the type of disease in acute cerebral infarction or the relationship between atherothrombotic cerebral infarction and the ratio of glycoalbumin / hemoglobin A1c. Moreover, although it has been reported that the blood glucose state at the onset of acute cerebral infarction and the prognosis are related (Non-patent Document 10), a study focusing on the ratio of glycoalbumin / hemoglobin A1c, the ratio of glycoalbumin / hemoglobin A1c There is no research on the use of disease type discrimination, determination of the presence or absence of onset, and prediction of onset.

NINDS (National Institute of Neurological Disorder and Stroke) “Classification of cerebrovascular diseases III”, Stroke 1990, Vol. 21, p. 637-676 Makoto Takagi, “Atherothrombotic cerebral infarction” (Stroke navigator, supervised by Yoshiyasu Kobayashi) Medical Review Co., Ltd. June 1, 2002, p126-127 Yasuhiro Tahara, “IV-B. Glycoalbumin (GA)” (Edited by Kenji Shima, seeing and thinking about blood glucose levels) Nankodo 2000 1/20 publication p62-69 Kazutomi Yoshiuchi (Glycated Albumin is a better Indication for Glucose Excursion) Glycated Albumin is a better Indication for Glucose Excursion than Glycated Hemoglobin in Type 1 and Type 2 Diabetes), Endcrine Journal, 2008, 155, p503-507 Nobuko Sakuma et al. "What is postprandial blood glucose and blood glucose fluctuation?", Obesity and diabetes, 2008, Vol. 7, No. 2, p818-820 Imai et al. “Improved Monitoring of the Hyperglycemic State in Type1 Diabetes Patients by Type 1 Diabetes Patiences Use of the Glycoalbuminn / HbA1c Ratio ”, The Review of Diabetic Studies, 2007, Volume 4, Issue 1, p44-48 Li Jin Pu et.al. “Increased Serum Glycated Albumin Level is Associated with the Presence and the Presence and the Presence and Severity of Coronary Artery Disease in Type 2 diabetic Patients.), Circulation Journal, 2007, Vol. 71, No. 7, p1067-1073 Masafumi Koga “Glycoalbumin / Fructosamine”, General Clinical, Vol. 57, No. 7, 2008, p1922-1927 Masafumi Koga et al. (Koga et. Al.) [Topics on Glycoalbumin], General Clinical, 2006, 55, 10, p2513-2514 Stesd LG et.al. "Hyperglycemia as an independent predictor of worse outcome in non-diabetic patients presenting with acute ischemic stroke), Neurocrit Care, 2009, 10, p181-186 52nd Annual Meeting of the Diabetes Society of Japan Poster Session Abstract IP-130 Hakodate Medical Journal Vol.28 No.1 (2004) p12

  The present invention relates to a method for performing disease type differentiation of atherothrombotic cerebral infarction in acute cerebral infarction accurately, simply, quickly and inexpensively, an apparatus for performing disease type differentiation, and an atheroma for disease type differentiation. It is an object to be solved to provide a kit for diagnosing thrombotic cerebral infarction. Furthermore, the present invention relates to a method for predicting the onset of atherothrombotic cerebral infarction accurately, simply, quickly and inexpensively, a measuring apparatus for predicting the onset of atherothrombotic cerebral infarction, and an atherothrombotic brain It is an object to be solved to provide an atherothrombotic cerebral infarction diagnostic kit for predicting the onset of infarction.

  We accidentally encountered a patient who had measured glycoalbumin and hemoglobin A1c for several years at our institution and developed an atherothrombotic cerebral infarction, and the patient's glycoalbumin / hemoglobin A1c ratio was atherothrombotic. It was found that there was a time series deviation from a characteristic value of about 3 from about 3 months before the onset of cerebral infarction. Based on the experience of this case, diagnosis of disease type was performed by 99 specialists such as neurologists, emergency physicians, radiologists, diabetics, etc. from images of medical history, physical findings, CT, MRI, etc. for 99 patients with acute cerebral infarction. Comprehensively conducted, classified into disease types, and cross-sectionally examined the relationship with the ratio of glycoalbumin / hemoglobin A1c. In atherothrombotic cerebral infarction among acute cerebral infarction, glycoalbumin / hemoglobin A1c is about 3 It was found that the value was statistically significantly higher than the characteristic value.

  That is, the present inventors measure glycoalbumin and hemoglobin A1c in a biological sample, and determine the glycoalbumin / hemoglobin A1c ratio and / or its change over time, thereby accurately and simply distinguishing the cerebral infarction from disease type. It has been found that it can be carried out at low cost and that it is possible to predict the onset of atherothrombotic cerebral infarction, and the present invention has been completed. To date, there has been no report showing a correlation between the diagnosis of cerebral infarction or prediction of the onset of acute cerebral infarction and the ratio of glycoalbumin / hemoglobin A1c. In the present invention, the ratio of glycoalbumin / hemoglobin A1c and / or its change over time has not been reported. Thus, it is epoch-making that it has been found for the first time that disease type discrimination of atherothrombotic cerebral infarction and onset prediction of atherothrombotic cerebral infarction can be carried out accurately, simply, quickly and inexpensively. According to the present invention, the following inventions are provided.

[1] When the ratio of glycoalbumin / hemoglobin A1c in a biological sample of a patient with acute cerebral infarction is used as an index, the atherothrombosis when the ratio of glycoalbumin / hemoglobin A1c is equal to or higher than the cut-off value for distinguishing atherothrombotic cerebral infarction A method of differentiating a disease type of atherothrombotic cerebral infarction in an acute cerebral infarction patient, characterized in that the cerebral infarction is determined.

[2] A method for differentiating a disease type of atherothrombotic cerebral infarction in an acute cerebral infarction patient, comprising the following steps (1) to (3);
(1) A step of measuring glycoalbumin and hemoglobin A1c in a biological sample of a patient with acute cerebral infarction;
(2) a step of calculating a glycoalbumin / hemoglobin A1c ratio from the measurement value obtained in step (1); and (3) a glycoalbumin / hemoglobin A1c ratio calculated in step (2) and atherothrombotic cerebral infarction. A step of comparing the cut-off value for disease type discrimination.

[3] The discrimination method according to [1] or [2], wherein the cut-off value for disease type discrimination is a numerical value arbitrarily set between 3 and 6, and the biological sample is a blood sample.
[4] The discrimination method according to [1] or [2], wherein the cut-off value for disease type discrimination is a numerical value arbitrarily set between 3.2 and 6, and the biological sample is a blood sample.

[5] Onset of atherothrombotic cerebral infarction when the ratio of glycoalbumin / hemoglobin A1c is greater than or equal to the cutoff value for predicting the onset of atherothrombotic cerebral infarction, using the ratio of glycoalbumin / hemoglobin A1c in the biological sample of the subject as an index A method for predicting the onset of atherothrombotic cerebral infarction, characterized in that it is determined that there is a high possibility that

[6] A method for predicting the onset of atherothrombotic cerebral infarction, comprising the following steps (1) to (3):
(1) a step of measuring glycoalbumin and hemoglobin A1c in the biological sample of the subject's biological sample;
(2) a step of calculating a glycoalbumin / hemoglobin A1c ratio from the measured value obtained in step (1); and (3) a glycoalbumin / hemoglobin A1c ratio calculated in step (2) and the onset of atherothrombotic cerebral infarction. A step of comparing the prediction cutoff value.

[7] The prediction method according to [5] or [6], wherein the onset prediction cutoff value is a numerical value arbitrarily set between 3 and 6, and the biological sample is a blood sample.
[8] The prediction method according to [5] or [6], wherein the onset prediction cutoff value is a numerical value arbitrarily set between 3.2 and 6, and the biological sample is a blood sample.

[9] (a) Glycoalbumin measurement unit, (b) Hemoglobin A1c measurement unit, (c) Calculation for calculating the ratio of glycoalbumin / hemoglobin A1c based on the measured glycoalbumin value and hemoglobin A1c value And (d) for identifying the type of atherothrombotic cerebral infarction in an acute stage cerebral infarction patient or predicting the onset of atherothrombotic cerebral infarction in a subject based on the calculated glycoalbumin / hemoglobin A1c ratio An apparatus for determining the type of atherothrombotic cerebral infarction in an acute cerebral infarction patient or predicting the onset of atherothrombotic cerebral infarction in a subject, comprising a determination unit.

[10] A kit for diagnosing atherothrombotic cerebral infarction comprising a glycoalbumin measurement reagent and a hemoglobin A1c measurement reagent, obtained by measurement with a glycoalbumin value obtained by measurement with a glycoalbumin measurement reagent and a hemoglobin A1c measurement reagent For determining the type of atherothrombotic cerebral infarction in acute cerebral infarction patients, or for predicting the onset of atherothrombotic cerebral infarction in subjects using the ratio of glycoalbumin / hemoglobin A1c calculated from the hemoglobin A1c value as an index Thrombotic cerebral infarction diagnostic kit.
[11] A method for predicting the onset of atherothrombotic cerebral infarction using the glycoalbumin / hemoglobin A1c ratio and its change over time in a biological sample of a subject as an index, and satisfying the following criteria, atherothrombotic cerebral infarction A prediction method characterized by determining that there is a high possibility of developing
1) The ratio of glycoalbumin / hemoglobin A1c is not less than the cutoff value for predicting the onset of atherothrombotic cerebral infarction, and
2) The amount of change per day in the ratio of 1) is within the time-dependent cut-off range for predicting the onset of atherothrombotic cerebral infarction.
[12] (a) Glycoalbumin measurement part, (b) Hemoglobin A1c measurement part, (c) Glycoalbumin / hemoglobin A1c ratio and change over time based on the measured glycoalbumin value and hemoglobin A1c value And (d) an atherothrombosis in the subject, comprising: (d) a determination portion for predicting the onset of atherothrombotic cerebral infarction in the subject based on the calculated glycoalbumin / hemoglobin A1c ratio and its change over time For predicting the onset of cerebral infarction.
[13] A kit for diagnosing atherothrombotic cerebral infarction comprising a glycoalbumin measurement reagent and a hemoglobin A1c measurement reagent, which is obtained by measurement using a glycoalbumin value obtained by measurement with a glycoalbumin measurement reagent and a hemoglobin A1c measurement reagent A kit for diagnosing atherothrombotic cerebral infarction for predicting the onset of atherothrombotic cerebral infarction in a subject using as an index the glycoalbumin / hemoglobin A1c ratio calculated from the hemoglobin A1c value and its change over time.

  Method for distinguishing atherothrombotic cerebral infarction in patients with acute cerebral infarction according to the present invention, apparatus for distinguishing atherothrombotic cerebral infarction in patients with acute cerebral infarction, and kit for diagnosing atherothrombotic cerebral infarction According to the present invention, it is possible to accurately, simply, quickly and inexpensively identify the disease type of acute cerebral infarction, which conventionally required complicated determinations by expensive devices and experts. Furthermore, according to the method for predicting the onset of atherothrombotic cerebral infarction according to the present invention, the predictive device for determining the onset of atherothrombotic cerebral infarction, and the kit for diagnosing atherothrombotic cerebral infarction, the onset prediction of atherothrombotic cerebral infarction is accurate and simple. Can be implemented quickly and inexpensively.

It is a disease type classification | category and test value of 99 patients of acute cerebral infarction based on the Example of this invention. It is a single regression analysis result about the factor which estimates atherothrombotic cerebral infarction based on the Example of this invention. It is a binomial logistic analysis result about the factor which estimates atherothrombotic cerebral infarction based on the Example of this invention. It is a ROC curve which calculates | requires the cut-off value of glycoalbumin / hemoglobin A1c ratio for pathological differentiation of atherothrombotic cerebral infarction based on the Example of this invention. It is a figure which shows the relationship between glycoalbumin and hemoglobin A1c in the diabetic patient who does not have the life related to the lifetime of 105 hemoglobin based on the Example of this invention, and the disease which concerns on the half life of albumin, and cerebral infarction.

Hereinafter, the present invention will be described more specifically.
(1) Glycoalbumin Glycoalbumin in the present invention is albumin in which albumin and glucose are bound non-enzymatically, and is sometimes called glycoalbumin or glycated albumin. Glycoalbumin can be measured by, for example, HPLC method, immunization method, enzyme method. Currently, for example, the enzyme method is widely used as a method for measuring glycoalbumin. The measurement of glycoalbumin in the present invention includes not only the measurement of the glycoalbumin concentration in the biological sample but also the measurement of the percentage of the glycoalbumin concentration in the biological sample with respect to the total albumin.

  In the enzyme method, for example, first, glycoalbumin in a biological sample is decomposed with a protease to produce a glycated amino acid. Next, ketoamine oxidase is reacted with the glycated amino acid, and the resulting hydrogen peroxide is reacted with peroxidase in the presence of a hydrogen donor and a dye to quantify the glycated amino acid. Furthermore, the glycoalbumin concentration in the biological sample can be obtained from the quantified glycated amino acid using a calibrator or the like having a known glycoalbumin concentration. The percentage (%) of glycoalbumin to total albumin can also be determined by determining the albumin concentration of the same biological sample by an albumin determination method such as the BCP improvement method and dividing the glycoalbumin concentration. In Japan, the Japanese Society for Clinical Chemistry recommends a standard method for measuring glycoalbumin (Takei et. Al., “JSCC Recommended Method for Measuring Glycoalbumin”, Clinical Chemistry, 2008, 37, 2, p178-191), and a measurement method having sufficient accuracy and accuracy in accordance with the standard method of glycoalbumin measurement.

(2) Hemoglobin A1c
In the present invention, hemoglobin A1c is hemoglobin in which glucose is non-enzymatically bound to the N-terminal valine of the hemoglobin β chain, and is sometimes referred to as hemoglobin A1c, HbA1c, glycohemoglobin, glycohemoglobin A1c, or the like. Hemoglobin A1c can be measured by, for example, HPLC method, immunological method, enzymatic method and the like. Currently, the HPLC method, the immunization method, and the enzymatic method are all widely used hemoglobin A1c measurement methods. The measurement of glycoalbumin in the present invention includes not only the measurement of the hemoglobin A1c concentration in the biological sample but also the measurement of the percentage of the hemoglobin A1c concentration in the biological sample with respect to the total hemoglobin.

  For example, the HPLC method uses a cation exchange column to separate and measure hemoglobin A1c in which β-chain N-terminal valine has been glycated from a biological sample, and obtain the percentage (%) of hemoglobin A1c with respect to the total hemoglobin in the biological sample. be able to. The immunological method is a method in which a peptide in which glucose is bound to β-chain N-terminal valine is used as an antigen, and the obtained antibody is used for measurement. The enzyme method may be a method of using a protease that cleaves a β-chain N-terminal peptide, and quantifying the cleaved glycated peptide by introducing it into a color development system using fructosipeptide oxidase. The measured value of hemoglobin A1c is standardized by the Japan Diabetes Society, the Japanese Society for Clinical Chemistry, etc., and is preferably a measurement method having sufficient accuracy and accuracy in accordance with the standardization. The glycoalbumin / hemoglobin A1c ratio means a numerical value obtained by dividing the measured value of glycoalbumin by the measured value of hemoglobin A1c.

(3) Disease classification of atherothrombotic cerebral infarction in acute cerebral infarction and prediction of onset of atherothrombotic cerebral infarction Acute cerebral infarction includes atherothrombotic cerebral infarction, cardiogenic cerebral embolism, lacunar infarction, etc. It is classified into four clinical types (NINDS “Classification of Cerebrovascular Diseases Version III”). Therefore, in the present invention, the disease type differentiation of atherothrombotic cerebral infarction in acute cerebral infarction is an act of determining whether or not the patient with acute cerebral infarction is classified as atherothrombotic cerebral infarction or the degree of probability And predicting the onset of atherothrombotic cerebral infarction means the act of determining whether or how likely a person will develop atherothrombotic cerebral infarction in the future.

  In the present invention, there is provided a method for distinguishing atherothrombotic cerebral infarction in acute cerebral infarction simply and accurately using the glycoalbumin / hemoglobin A1c ratio in a biological sample derived from an acute cerebral infarction patient as an index. It is more preferable to perform the discrimination by using a conventional discrimination method from the viewpoint of further improving the discrimination accuracy.

  As a conventional discrimination method, a comprehensive method using medical history, physical findings, CT, MRI images, and the like by a plurality of specialists such as a neurologist, an emergency doctor, a radiologist, a diabetic, and the like can be exemplified. As a medical history, hypertension, diabetes, hyperlipidemia, smoking, drinking habits, presence or absence of heart disease, etc. are important for conventional discrimination. For example, if there is a risk factor for atherosclerosis such as hypertension, diabetes, hyperlipidemia, smoking, etc., if there is complication of other atherosclerotic diseases, TIA precedent, cervical vascular noise, etc., atherothrombotic cerebral infarction Suspected. In atherothrombotic cerebral infarction, arteriosclerosis gradually progresses, so there are many mild cases such as mild paralysis at the beginning of the onset. On the other hand, cardiogenic cerebral infarction is suspected if there is a heart disease of embolism, sudden onset type onset, severe consciousness disturbance at the time of onset, and the like. CT and MRI are used to check for bleeding and to distinguish between bleeding and infarction and the range of the infarct. Cardiogenic cerebral infarction may present with extensive or hemorrhagic infarction. Lacunar infarction is defined as a small infarction with a major axis of less than 1.5 cm that can explain neurological symptoms. In recent years, it is diagnosed by DWI.

(4) Cutoff value for distinguishing atherothrombotic cerebral infarction, cutoff value for predicting onset of atherothrombotic cerebral infarction, and time-dependent cut-off range for predicting onset of atherothrombotic cerebral infarction Atherothrombotic cerebral infarction The cut-off value for disease type discrimination and the cut-off value for predicting the onset of atherothrombotic cerebral infarction are described in detail below.
Generally, it is known that the amount ratio of glycoalbumin / hemoglobin A1c in the blood of a diabetic patient becomes a characteristic value of about 3 in a state where blood sugar is stable (Non-patent Document 3). In the present invention, 105 diabetic patients with stable blood glucose for at least 3 months without administration of drugs such as steroids or erythropoietin that affect liver disease, kidney disease, thyroid disease, anemia, protein synthesis ( Glycoalbumin characteristic blood glucose in a stable state from the measured value of glycoalbumin and hemoglobin A1c in the blood glucose stability period (intermediate month of the above stable period) in patients whose hemoglobin A1c fluctuation is 3% or less in 3 months An albumin / hemoglobin A1c ratio of 2.90 was determined. Therefore, the ratio of glycoalbumin / hemoglobin A1c in a state where blood sugar is stable may be 2.90. Note that the characteristic value of about 3 of glycoalbumin / hemoglobin A1c in diabetic patients with stable blood sugar is the race, gender, age, population of cases, unit of measurement by international standardization in the future, etc. May change depending on the change.

  The cut-off value for disease type discrimination of atherothrombotic cerebral infarction means a reference value of the ratio of glycoalbumin / hemoglobin A1c in order to obtain whether or not the patient has atherothrombotic cerebral infarction or the degree of probability. . The cut-off value for predicting the onset of atherothrombotic cerebral infarction means a reference value of the ratio of glycoalbumin / hemoglobin A1c to obtain whether or not the patient will suffer from atherothrombotic cerebral infarction in the future. Any cutoff value can be a single or multiple numerical values.

  Any cut-off value can be any numerical value between 2.9-6, 3-6, preferably 3.2-6, more preferably 3.2-4. Glycoalbumin / hemoglobin A1c ratio of a diabetic patient in a stable blood glucose state is characteristically about 3.0 (2.9 in the present embodiment), and deviates from this characteristic value in the process of completing atherothrombotic cerebral infarction. Therefore, for example, it can be a numerical value of 1 or more selected from 2.9, 3.0, 3.2, 3.22. Alternatively, for example, 20 or more (preferably 30, more preferably 50 or more, most preferably 70 or more) acute cerebral infarction patients are treated with atherothrombotic cerebral infarction patients, cardiogenic cerebral infarction or lacunar infarction. Glycoalbumin is identified for patients of various categories such as atherothrombotic cerebral infarction, cardiogenic cerebral infarction, lacunar infarction, etc., as distinguished from patients by conventional methods (eg, medical history, physical findings, CT, MRI images, etc.) And hemoglobin A1c may be measured, and the ratio of glycoalbumin / hemoglobin A1c may be determined for each disease type to obtain a cutoff value. Further, a cutoff value may be obtained by a known statistical method (ROC curve or the like) (Example). In Examples of the present application, 3.2 and 3.22 were obtained as the disease type discrimination cut-off values for atherothrombotic cerebral infarction by such a method. The cutoff value or the cutoff value for predicting the onset of atherothrombotic cerebral infarction is preferably 3.2 or 3.22.

  Comparison between glycoalbumin / hemoglobin A1c ratio obtained by measurement and cut-off value for disease type discrimination of thrombotic cerebral infarction or cut-off value for predicting onset of atherothrombotic cerebral infarction, and further discrimination based on the comparison Or performing onset prediction is explained in full detail below.

  When the cut-off value for disease type discrimination of atherothrombotic cerebral infarction is one numerical value, the ratio of the measured values of glycoalbumin and hemoglobin A1c in a biological sample of a patient with acute cerebral infarction is greater than or equal to the cut-off value In addition, patients with acute cerebral infarction can be identified as having or likely to have atherothrombotic cerebral infarction, and conversely, if they are less than the cut-off value, they are not affected or likely Can be identified as low.

  For example, when the cut-off value for disease type discrimination of atherothrombotic cerebral infarction is 3.2 or 3.22, the ratio of glycoalbumin / hemoglobin A1c measured using a biological sample is 3.2 or 3.22 or more The patient with acute cerebral infarction who provided the biological sample in the case of is an atherothrombotic cerebral infarction patient or is highly likely, and if it is less than 3.2 or 3.22, the patient is not an atherothrombotic cerebral infarction patient Or it can be identified that the probability is low.

  When the cut-off value for predicting the onset of atherothrombotic cerebral infarction is a single numerical value, if the ratio of the measured value of glycoalbumin to hemoglobin A1c in a biological sample of the person is greater than or equal to the cut-off value, the person will It can be predicted that the patient will suffer from or is highly likely to have thrombotic cerebral infarction, and conversely, if the person is less than the cut-off value, the person is predicted not to suffer from or suffer from atherothrombotic cerebral infarction in the future. can do. For example, when the cutoff value for predicting the onset of atherothrombotic cerebral infarction is 2.9 or 3.0, the ratio of glycoalbumin / hemoglobin A1c measured using a biological sample is 2.9 or 3.0 or more The person who provided the biological sample in the future will suffer from or is likely to suffer from atherothrombotic cerebral infarction patients in the future, and if it is less than 2.9 or 3.0, it will not or will not suffer from future atherothrombotic cerebral infarction patients Can be expected to be low.

  When the cut-off value for distinguishing the type of atherothrombotic cerebral infarction is a plurality of numerical values, the presence or absence of atherothrombotic cerebral infarction or the degree of its probability can be differentiated in multiple stages. For example, if the cutoff value is set to A1, A2, A3, ..., An, and less than A1, A1 to A2, A2 to A3, ..., An-1 to An, and An It is also possible to set a range of glycoalbumin / hemoglobin A1c ratios in multiple stages and predict that the probability of onset is higher as the numerical range is larger. For example, when the cut-off value for disease type discrimination of atherothrombotic cerebral infarction is 3.00, 3.22, and the ratio of glycoalbumin / hemoglobin A1c measured using a biological sample is 3.22 or more has developed or The probability is high, 3.00 to 3.22 is likely to be onset, and 3.00 or less can be identified as low probability of onset.

  When the cut-off value for predicting the onset of atherothrombotic cerebral infarction is a plurality of numerical values, the possibility of the onset of atherothrombotic cerebral infarction can be predicted in multiple stages. For example, if the cutoff value is set to A1, A2, A3, ..., An, and less than A1, A1 to A2, A2 to A3, ..., An-1 to An, and An It is also possible to set a range of glycoalbumin / hemoglobin A1c ratios in multiple stages and predict that the possibility of future onset is higher as the numerical range is larger. For example, the cut-off value for predicting the onset of atherothrombotic cerebral infarction is 3.00, 3.22, and if the ratio of glycoalbumin / hemoglobin A1c measured using a biological sample is 3.22 or higher, or will be possible in the future It is possible to predict that 3.00 to 3.22 is likely to develop in the future, and 3.00 or less is unlikely to develop in the future.

  It should be noted that the glycoalbumin / hemoglobin A1c ratio measured using a biological sample was compared with the cut-off for determining the disease type of atherothrombotic cerebral infarction. As a result, the presence or absence of atherothrombotic cerebral infarction or the possibility thereof The method for differentiating the degree of is not limited to the above method, the ratio of glycoalbumin / hemoglobin A1c measured using a biological sample and the cut-off value for predicting the onset of atherothrombotic cerebral infarction, The method for predicting the future development of atherothrombotic cerebral infarction is not limited to the above method.

  Furthermore, differentiation of patients with acute cerebral infarction can also be carried out using the “method for distinguishing the type of atherothrombotic cerebral infarction in patients with acute cerebral infarction” according to the present invention. That is, when a method for differentiating the type of atherothrombotic cerebral infarction is identified and a patient with acute cerebral infarction is identified as not having or unlikely having atherothrombotic cerebral infarction, the acute brain Whether an infarcted patient corresponds to cardiogenic cerebral infarction, lacunar infarction, or other acute phase cerebral infarction can be differentiated using a method known per se (such as CT or other image diagnosis). In addition, since the quantity ratio of glycoalbumin / hemoglobin A1c in the blood of diabetic patients is a characteristic value of about 3, the subject providing the biological sample in the method for predicting the onset of atherothrombotic cerebral infarction From the viewpoint of prediction accuracy and the like, it is preferable that the patient has sclerosis and a patient having risk factors for atherothrombotic cerebral infarction such as a diabetic patient.

  The time-dependent cut-off range for predicting the onset of atherothrombotic cerebral infarction is described in detail below.

  As described above, the onset of atherothrombotic cerebral infarction can be predicted based on the contrast between the measured glycoalbumin / hemoglobin A1c ratio and the cut-off value for predicting the onset of atherothrombotic cerebral infarction. As described above, the onset of atherothrombotic cerebral infarction can also be predicted based on the contrast between the measured time-dependent change in glycoalbumin / hemoglobin A1c ratio and the time-dependent cut-off range for predicting the onset of atherothrombotic cerebral infarction.

  The time-dependent cut-off range for predicting the onset of atherothrombotic cerebral infarction is a criterion for the time-dependent change in the ratio of glycoalbumin / hemoglobin A1c to obtain whether or not the patient will suffer from atherothrombotic cerebral infarction in the future. Mean value. The temporal change in the ratio of glycoalbumin / hemoglobin A1c means a temporal change in the ratio of glycoalbumin / hemoglobin A1c in samples of the same living tissue derived from the same subject. The temporal change can be, for example, an increase / decrease value of the ratio of glycoalbumin / hemoglobin A1c per hour, day, or month.

  The time-dependent cutoff range for predicting the onset of atherothrombotic cerebral infarction is, for example, 0.005 to 0.03 / day, preferably 0.008 to 0.02 / day, and more preferably 0.01 to 0.015. / Day.

  A sample of the same living tissue (for example, a blood sample) can be continuously or irregularly collected from a certain person, and the change over time in the ratio of glycoalbumin / hemoglobin A1c in the sample can be observed. Is included in the time-dependent cut-off range for predicting the development of atherothrombotic cerebral infarction, it can be predicted that the person will suffer from or is likely to have atherothrombotic cerebral infarction in the future. If not in the cut-off range, it can be predicted that the person will not suffer from or is unlikely to suffer from atherothrombotic cerebral infarction in the future. When a sample is taken three or more times consecutively from the person, theoretically, a plurality of time-varying values are observed, but in that case, the maximum value among them is the time-dependent change in the ratio of glycoalbumin / hemoglobin A1c. It can be.

  Specifically, for example, a blood sample of a person is periodically collected every 30 days, and the ratio of glycoalbumin / hemoglobin A1c in the blood sample changes to A, B, C, D,. , (A-B) / 30 days, (BC) / 30 days, (C-D) / 30 days,... Maximum value (time-dependent change) and time for predicting the onset of atherothrombotic cerebral infarction By contrasting the change cut-off range, if the time course is 0.005-0.03 / day, one can predict that the person will suffer from or is likely to have atherothrombotic cerebral infarction in the future .

  In addition, the time-dependent changes in the ratio of glycoalbumin / hemoglobin A1c in the biological sample of a certain person at a certain time point and the ratio up to that time point are used for predicting the onset of atherothrombotic cerebral infarction and for predicting the onset of atherothrombotic cerebral infarction, respectively. Contrast with the time-dependent cutoff range 1) The ratio is equal to or greater than the cut-off value for predicting the onset of atherothrombotic cerebral infarction, and the time-dependent change is the time-dependent cut-off range for predicting the onset of atherothrombotic cerebral infarction Can be predicted that the person will or will likely have atherothrombotic cerebral infarction in the future, 2) the ratio is less than the cut-off value for predicting the onset of atherothrombotic cerebral infarction, or If the change over time is outside the time-dependent cut-off range for predicting the onset of atherothrombotic cerebral infarction, the person It can be predicted without suffering from cerebral infarction or that there is a low possibility.

  Specifically, for example, if a blood sample of a person is periodically collected every 30 days and the ratio of glycoalbumin / hemoglobin A1c in the blood sample is changed to A, B, C, D, (A− B) / 30 days, (BC) / 30 days, if the maximum value of (CD) / 30 days is a change over time, D is equal to or greater than the cutoff value for predicting the onset of atherothrombotic infarction, And when the said time-dependent change is contained in the time-dependent cut-off range for the onset prediction of an atherothrombotic cerebral infarction, it can be estimated that the person will suffer from an atherothrombotic cerebral infarction in the future or its possibility is high.

(5) Apparatus of the present invention The apparatus for distinguishing the type of atherothrombotic cerebral infarction according to the present invention or the apparatus for predicting the onset of atherothrombotic cerebral infarction is a measurement unit of glycoalbumin, measurement of hemoglobin A1c. A calculation unit for calculating the measured glycoalbumin / hemoglobin A1c ratio (and / or its change over time), and differentiation or prediction based on the glycoalbumin / hemoglobin A1c ratio (and / or its change over time) Any device can be used as long as the device includes a determination unit for performing the above.

  The glycoalbumin measurement unit is a site for measuring glycoalbumin in a biological sample introduced into the apparatus. The measurement part of hemoglobin A1c is a site | part which measures hemoglobin A1c in the biological sample introduced into the apparatus. There are no particular limitations on the size, configuration, etc. of these parts, and these measurements are not particularly limited as long as each protein in a biological sample is measured. For example, the conventional use of glycoalbumin or hemoglobin A1c described above is not limited. It can be done with a measuring method.

  As a method for measuring glycoalbumin, in addition to the HPLC method, immunization method, enzyme method, etc., electrophoresis method, electrode method, etc. may be used, and other methods may be used. For example, the measurement of glycoalbumin may use an enzyme method that is widely used. Enzymatic methods are, for example, by decomposing glycoalbumin of a target sample with a protease, then reacting ketoamine oxidase with glycated lysine and reacting with a dye to determine the concentration of glycoalbumin, and determining the concentration of glycoalbumin. In this method, glycoalbumin (%) can be measured by measuring the albumin concentration and dividing by the albumin concentration. Other commercially available reagents, known methods, and reagents may be used. Moreover, the measurement of hemoglobin A1c may use the HPLC method and the immunization method which are widespread. In the HPLC method, for example, hemoglobin A1c is separated and fractionated by an ion exchange column, and the concentration (%) can be calculated.

  The calculation unit is a part that divides the glycoalbumin value obtained by measurement by the glycoalbumin measurement unit by the hemoglobin A1c value obtained by measurement by the hemoglobin A1c measurement unit, for example, a central processing unit provided in the apparatus (CPU). Note that the glycoalbumin value and the hemoglobin A1c value may be stored in a storage device provided in the device such as a memory or a hard disk after both measurements and before the calculation, or the division value in the calculation unit is temporarily stored in the storage device. May be memorized.

  Based on the glycoalbumin / hemoglobin A1c ratio (and / or temporal change in the ratio) obtained by the calculation unit, the determination unit distinguishes the type of atherothrombotic cerebral infarction in patients with acute cerebral infarction or atherothrombotic cerebral infarction This is a site for predicting the onset.

  In the present apparatus, the disease type discrimination of atherothrombotic cerebral infarction can be performed by comparing the glycoalbumin / hemoglobin A1c ratio obtained by the calculation unit with the cut-off value for disease type discrimination of atherothrombotic cerebral infarction. The cut-off value for disease type discrimination of atherothrombotic cerebral infarction may be stored in the device in advance, or may be input from the input site of the device at the time of discrimination. As a result of the comparison, for example, when the glycoalbumin / hemoglobin A1c ratio obtained by the calculation unit is equal to or higher than the cut-off value for disease type discrimination of atherothrombotic cerebral infarction, the person who provided the biological sample becomes atherothrombotic cerebral infarction. The person who provided the biological sample is suffering from atherothrombotic cerebral infarction if it can be identified as being affected or likely to be affected, and conversely, if it is less than the cut-off value for disease type discrimination of atherothrombotic cerebral infarction It can be discriminated that there is no or low probability. Cutoff values for atherothrombotic cerebral infarction disease type discrimination can be set to a single device or multiple devices, and when multiple cut-off values are set, differentiation is performed in multiple stages as described above. It can also be done.

  In the present apparatus, the onset prediction of atherothrombotic cerebral infarction can be carried out by comparing the glycoalbumin / hemoglobin A1c ratio obtained by the calculation unit with the cut-off value for predicting the onset of atherothrombotic cerebral infarction. The cut-off value for predicting the onset of atherothrombotic cerebral infarction may be stored in advance in the apparatus, or may be input from an input site of the apparatus at the time of prediction. As a result of the comparison, for example, when the ratio of glycoalbumin / hemoglobin A1c obtained in the calculation unit is equal to or higher than the cut-off value for predicting the onset of atherothrombotic cerebral infarction, the person who provided the biological sample will have atherothrombotic cerebral infarction in the future. On the other hand, the person who provided the biological sample will not develop or be able to develop atherothrombotic cerebral infarction in the future if it is predicted that it will develop or is highly likely to occur, and conversely, if it is less than the cutoff value for predicting the onset of atherothrombotic cerebral infarction Can be predicted to be low. The cut-off value for predicting the onset of atherothrombotic cerebral infarction can be set to a single device or multiple devices, and the prediction when multiple cut-off values are set is multistage as described above. You can also do it.

  Alternatively, in the present apparatus, the onset prediction of atherothrombotic cerebral infarction may be performed by comparing the time-dependent change in glycoalbumin / hemoglobin A1c ratio obtained by the calculation unit with the time-dependent cut-off range for predicting the onset of atherothrombotic cerebral infarction. Can be implemented. The time-varying cut-off range for predicting the onset of atherothrombotic cerebral infarction may be stored in advance in the apparatus, or may be input from an input site of the apparatus at the time of prediction. As a result of the comparison, for example, when the time-dependent change in the ratio of glycoalbumin / hemoglobin A1c obtained in the calculation unit is included in the time-dependent cut-off range for predicting the onset of atherothrombotic cerebral infarction, the person who provided the biological sample Who is expected to develop or is likely to develop atherothrombotic cerebral infarction in the future, and conversely, who is not included in the time-dependent cut-off range for predicting the development of atherothrombotic cerebral infarction Can be predicted not to develop or be unlikely to develop atherothrombotic cerebral infarction in the future.

  Further, in this apparatus, the onset prediction of atherothrombotic cerebral infarction is carried out by determining the glycoalbumin / hemoglobin A1c ratio obtained by the calculation unit and the change over time of the ratio, the cut-off value for predicting the onset of atherothrombotic cerebral infarction and the atheroma, respectively. This can be done by comparing with a time-dependent cutoff range for predicting the onset of thrombotic cerebral infarction. The cut-off value for predicting the onset of atherothrombotic cerebral infarction and the time-dependent cut-off range for predicting the onset of atherothrombotic cerebral infarction may be stored in advance in the device, or input from the input site of the device at the time of prediction May be. As a result of the comparison, for example, the glycoalbumin / hemoglobin A1c ratio obtained in the calculation unit and the change over time of the ratio are each equal to or higher than the cut-off value for predicting the onset of atherothrombotic cerebral infarction and the onset of atherothrombotic cerebral infarction If included in the predictive chronological cut-off range, it can be predicted that the person who provided the biological sample will develop or is likely to develop atherothrombotic cerebral infarction in the future, and conversely, the ratio is atherothrombotic cerebral infarction. If it is less than the cut-off value for predicting the onset of the disease, or the change over time in the ratio is not within the cut-off range for predicting the onset of atherothrombotic cerebral infarction, the person who provided the biological sample may It can be predicted that atherothrombotic cerebral infarction will not develop or is less likely to develop.

  The apparatus may include an output unit. The output unit performs processing such as displaying or outputting the disease type discrimination or onset prediction result on a display device such as a display or a printing device such as a printer.

  This apparatus is preferably a POC inspection apparatus (generally, an apparatus for inspecting immediately next to a patient (for example, at the bedside) in a clinical setting) from the viewpoint of convenience and the like.

(6) Kit for diagnosing atherothrombotic cerebral infarction of the present invention The glycoalbumin measuring reagent contained in the kit for diagnosing atherothrombotic cerebral infarction of the present invention can be measured as long as it is a reagent capable of measuring glycoalbumin in a biological sample. The method (HPLC method, immunization method, enzyme method, etc.) and the composition of the reagent are not particularly limited. As a measuring method, an enzyme method can be preferably exemplified. For example, Lucika GA or Lucika GA-L (both manufactured by Asahi Kasei Co., Ltd.) employing an enzymatic method can be preferably exemplified as a glycoalbumin measurement reagent.

  As long as the hemoglobin A1c measurement reagent contained in the kit for diagnosing atherothrombotic cerebral infarction of the present invention is a reagent capable of measuring hemoglobin A1c in a biological sample, a measurement method (HPLC method, immunization method, enzyme method, etc.) or reagent There is no particular limitation on the configuration of the above. The measurement of hemoglobin A1c is standardized by the Japan Diabetes Society or related societies, and is preferably a measurement adapted to this standardization. For example, a thunk HbA1c (manufactured by Arkray) employing an enzyme method can be mentioned.

  The kit for diagnosing atherothrombotic cerebral infarction of the present invention is measured using glycoalbumin in a biological sample measured using a glycoalbumin measuring reagent contained in this kit and a hemoglobin A1c measuring reagent contained in this kit. The ratio of hemoglobin A1c in a biological sample (glycoalbumin / hemoglobin A1c ratio) (and / or the change in the ratio over time) is used as an index to identify the type of atherothrombotic cerebral infarction or to predict its onset. The As described above, the disease type discrimination or the onset prediction thereof may be compared with the atherothrombotic cerebral infarction cut-off value or atherothrombotic cerebral infarction cut-off value or atherothrombotic cerebral infarction It can be implemented by comparison with the time course cut-off range for predicting the onset.

  The biological sample to be measured in the present invention may be any sample as long as it is a test solution containing at least hemoglobin and glycated protein. Preferred types of test liquid include blood components such as serum, plasma, blood cells, whole blood, or separated red blood cells. Serum and plasma may be separated by a normal method. The biological sample can be easily obtained by a method known per se, and the biological sample may be pretreated by a conventional method.

  The present invention will be described more specifically with reference to the following examples, but the present invention is not limited to the examples.

[Example 1]
A total of 99 patients with acute cerebral infarction were evaluated by neurologists, emergency physicians, radiologists, and diabetics based on medical history, physical findings, CT, MRI images, and the like. As a result of identifying 99 cases, there were 38 patients with atherothrombotic cerebral infarction, 37 cases with cardiogenic cerebral infarction, and 24 cases with lacunar infarction. FIG. 1 shows the age, sex, BMI, presence / absence of smoking, and other data. The glycoalbumin / hemoglobin A1c ratio of patients with atherothrombotic cerebral infarction was 3.2, which was significantly higher than that of patients with cardiogenic cerebral infarction and lacunar infarction (P <0.001).

  When the factors for estimating atherothrombotic cerebral infarction were determined by single regression analysis from the various measurement results shown in FIG. 2, the ratio of glycoalbumin / hemoglobin A1c was P <0.001, which is an explanatory variable for atherothrombotic cerebral infarction. It turned out to be. Furthermore, as a result of binomial logistic analysis for the explanatory variable showing P value <0.2, it was found that the ratio of glycoalbumin / hemoglobin A1c is an independent explanatory variable (FIG. 3). From the above results, it was found that atherothrombotic cerebral infarction can be identified by the ratio of glycoalbumin / hemoglobin A1c.

  Using data on the ratio of glycoalbumin / hemoglobin A1c of 99 patients with acute cerebral infarction, the ratio of glycoalbumin / hemoglobin A1c for differentiating atherothrombotic cerebral infarction was determined from the ROC curve. The results of the ROC curve are shown in FIG. From FIG. 4, 3.22 was obtained as a judgment value for distinguishing atherothrombotic cerebral infarction (a cut-off value for disease type discrimination of atherothrombotic cerebral infarction). When the disease type of an acute cerebral infarction patient is determined using the glycoalbumin / hemoglobin A1c ratio of 3.22 as a discriminant value, the sensitivity is 91.7% and the sensitivity is high, and the specificity is 95.0% and the efficiency of the false positive is low. A good judgment was possible.

  Based on the above, it is possible to perform differentiation of atherothrombotic cerebral infarction both in terms of sensitivity and specificity by measuring glycoalbumin and hemoglobin A1c and determining the ratio of glycoalbumin / hemoglobin A1c in patients with acute cerebral infarction. In the past, it was possible to easily, rapidly and inexpensively identify the type of acute cerebral infarction, which required a highly specialized, complicated and expensive device.

  The blood of 105 diabetic patients who did not have a disease related to the lifetime of hemoglobin and the half-life of albumin was collected with a normal blood collection tube, and glycoalbumin and hemoglobin A1c were measured. Glycoalbumin was measured using an enzymatic method, and hemoglobin A1c was measured using an HPLC method. FIG. 5 shows the relationship between glycoalbumin and hemoglobin A1c in 105 diabetic patients who do not have a cerebral infarction or a disease related to the lifetime of hemoglobin and the half-life of albumin. The glycoalbumin / hemoglobin A1c ratio for these patients was 2.90.

  In a state where the blood glucose state is stable, the ratio of glycoalbumin / hemoglobin A1c is 2.90, and may be higher than 2.90 in the process of completion of atherothrombotic cerebral infarction. In the target patient, it is possible to predict the onset of atherothrombotic cerebral infarction by the glycoalbumin / hemoglobin A1c ratio.

  For example, the ratio of glycoalbumin / hemoglobin A1c at the time of onset of a patient with atherothrombotic cerebral infarction is 4.30, which is significantly higher than the characteristic value of about 3; The hemoglobin A1c ratio was 4.15, and the glycoalbumin / hemoglobin A1c ratio 3 months before the onset was 3.39, which increased as it approached the onset of atherothrombotic cerebral infarction.

  By regularly monitoring the glycoalbumin / hemoglobin A1c ratio, it is possible to predict the onset of atherothrombotic cerebral infarction.

  For example, the onset can be predicted using the ratio of glycoalbumin / hemoglobin A1c as an index. Specifically, a glycoalbumin / hemoglobin A1c ratio of 3.22 or higher is likely to develop, 3.00 to 3.22 is likely to develop, 3.00 or less is less likely to develop, etc. Evaluation evaluation may be performed.

  Alternatively, it is possible to predict the onset using the change with time of the glycoalbumin / hemoglobin A1c ratio itself as an index. That is, it can be determined that the possibility of onset is high when the change over time is in the cut-off range for predicting the onset of atherothrombotic cerebral infarction. For example, when the ratio change over time is 0.005 to 0.03 / day, preferably 0.008 to 0.02 / day, more preferably 0.01 to 0.015 / day, It can be determined that the possibility is high. In the above example, the increase in the ratio is observed at a pace of (4.15-3.39) / about 60 days = about 0.013 / day between 3 months before onset and 1 month before onset. By monitoring the ratio between 3 months before onset and 1 month before onset, it can be determined that the possibility of onset is high.

  The onset can also be predicted using the combination of glycoalbumin / hemoglobin A1c ratio and its change over time as an index. For example, when the ratio is 3.22 or more and the time change is included in the range of 0.1 to 0.15 / day, it can be determined that the possibility of onset is high. As explained in the above example, the glycoalbumin / hemoglobin A1c ratio 3 months before the onset is 3.39, which is high, so doctors etc. start regular monitoring of this patient from this point or earlier Preferably, the patient can then be determined to have a high probability of developing atherothrombotic cerebral infarction when the increase in daily ratio reaches 0.1-0.15 / day.

  Alternatively, other evaluation determination methods may be used.

  In the present invention, glycoalbumin and hemoglobin A1c are measured, and the ratio of glycoalbumin / hemoglobin A1c is determined, whereby the disease type differentiation of acute cerebral infarction can be performed with good sensitivity and specificity, simply, quickly and inexpensively. It can be carried out. Further, in the present invention, the onset prediction of atherothrombotic infarction can be performed with good sensitivity and specificity, simply, quickly and inexpensively. The methods, devices and reagents of the present invention are useful in clinical testing.

Claims (13)

Using the ratio of glycoalbumin / hemoglobin A1c in a biological sample of an acute cerebral infarction patient as an index, when the ratio of glycoalbumin / hemoglobin A1c is equal to or higher than the cut-off value for distinguishing atherothrombotic cerebral infarction, atherothrombotic cerebral infarction A method for assisting in differentiating a disease type of atherothrombotic cerebral infarction in a patient with acute cerebral infarction, characterized in that A method for assisting in identifying a disease type of atherothrombotic cerebral infarction in an acute cerebral infarction patient, comprising the following steps (1) to (3);
(1) A step of measuring glycoalbumin and hemoglobin A1c in a biological sample of a patient with acute cerebral infarction;
(2) a step of calculating a glycoalbumin / hemoglobin A1c ratio from the measurement value obtained in step (1); and (3) a glycoalbumin / hemoglobin A1c ratio calculated in step (2) and atherothrombotic cerebral infarction. A step of comparing the cut-off value for disease type discrimination. The differentiation assisting method according to claim 1 or 2, wherein the cut-off value for disease type identification is a numerical value arbitrarily set between 3 and 6, and the biological sample is a blood sample. The differentiation assisting method according to claim 1 or 2, wherein the cut-off value for disease type identification is a numerical value arbitrarily set between 3.2 and 6, and the biological sample is a blood sample. Possibility of developing atherothrombotic cerebral infarction when the ratio of glycoalbumin / hemoglobin A1c is greater than or equal to the cutoff value for predicting the onset of atherothrombotic cerebral infarction, using the ratio of glycoalbumin / hemoglobin A1c in the biological sample of the subject as an index A method for predicting the onset of atherothrombotic cerebral infarction, characterized in that it is determined to be high. A method for predicting the onset of atherothrombotic cerebral infarction, comprising the following steps (1) to (3);
(1) a step of measuring glycoalbumin and hemoglobin A1c in the biological sample of the subject's biological sample;
(2) a step of calculating a glycoalbumin / hemoglobin A1c ratio from the measured value obtained in step (1); and (3) a glycoalbumin / hemoglobin A1c ratio calculated in step (2) and the onset of atherothrombotic cerebral infarction. A step of comparing the prediction cutoff value. The prediction method according to claim 5 or 6, wherein the onset prediction cutoff value is a numerical value arbitrarily set between 3 and 6, and the biological sample is a blood sample. The prediction method according to claim 5 or 6, wherein the onset prediction cutoff value is a numerical value arbitrarily set between 3.2 and 6, and the biological sample is a blood sample. (A) Glycoalbumin measurement unit, (b) Hemoglobin A1c measurement unit, (c) Glycoalbumin / hemoglobin A1c ratio calculation unit based on the measured glycoalbumin value and hemoglobin A1c value, and (D) based on the calculated glycoalbumin / hemoglobin A1c ratio, and having a determination unit that performs atherothrombotic cerebral infarction type discrimination in acute cerebral infarction patients, or predicts the onset of atherothrombotic cerebral infarction in subjects, An apparatus for identifying a disease type of atherothrombotic cerebral infarction in an acute cerebral infarction patient or predicting the onset of atherothrombotic cerebral infarction in a subject. A kit for diagnosing atherothrombotic cerebral infarction, comprising a reagent for measuring glycoalbumin and a reagent for measuring hemoglobin A1c, wherein the value of glycoalbumin obtained by measurement with the reagent for measuring glycoalbumin and hemoglobin A1c obtained by measurement with the reagent for measuring hemoglobin A1c Atherothrombotic brain for identifying the type of atherothrombotic cerebral infarction in patients with acute cerebral infarction, or for predicting the onset of atherothrombotic cerebral infarction in a subject using the ratio of glycoalbumin / hemoglobin A1c calculated by the value as an index Infarct diagnosis kit. A method for predicting the onset of atherothrombotic cerebral infarction using the glycoalbumin / hemoglobin A1c ratio in a biological sample of a subject and its change over time as an index, and developing atherothrombotic cerebral infarction when the following criteria are satisfied A prediction method characterized by determining that the possibility is high;
1) The ratio of glycoalbumin / hemoglobin A1c is not less than the cutoff value for predicting the onset of atherothrombotic cerebral infarction, and
2) The daily increase in the ratio of 1) is within the time-dependent cut-off range for predicting the onset of atherothrombotic cerebral infarction. (A) Glycoalbumin measurement part, (b) Hemoglobin A1c measurement part, (c) Glycoalbumin / hemoglobin A1c ratio and its change with time are calculated based on the measured glycoalbumin value and hemoglobin A1c value. Onset of atherothrombotic cerebral infarction in the subject, comprising: a computing unit; and (d) a judgment unit for predicting onset of atherothrombotic cerebral infarction in the subject based on the calculated glycoalbumin / hemoglobin A1c ratio and its change over time A device for making predictions. A kit for diagnosing atherothrombotic cerebral infarction, comprising a reagent for measuring glycoalbumin and a reagent for measuring hemoglobin A1c, wherein the value of glycoalbumin obtained by measurement with the reagent for measuring glycoalbumin and hemoglobin A1c obtained by measurement with the reagent for measuring hemoglobin A1c A kit for diagnosing atherothrombotic cerebral infarction for predicting the onset of atherothrombotic cerebral infarction in a subject using the ratio of glycoalbumin / hemoglobin A1c calculated by the value and its change over time as an index.

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